United States

We tested a new method for presenting natural materials using an electrostatic tactile texture display. In this method, we combined Coulomb friction as physical model for low frequency friction and texture-induced vibration model for high frequency friction. In a condition where only the low-frequency friction force components were rendered, the materials were correctly recognized at 70%. In contrast, when the high-frequency components were superposed, this rate increased to 80%. Therefore, Coulomb friction model plus fine texture improves material discrimination accuracy.

IEEE RO-MAN 2021

Virtual Tactile Texture Using Electrostatic Friction Display for Natural Materials: The Role of Low and High Frequency Textural Stimuli

natural materials

auto-regressive model

electrostatic friction stimuli

tactile texture display

**31st IEEE International Conference on Robot & Human Interactive Communication**
 This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.
 
 The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.
 
 **CONFERENCE THEME:**
 Social, asocial, and antisocial robots
 
 Robots are starting to populate our lives: at work, in our homes, hotels, shops. However, not everybody is comfortable with robots finding a place in society. For example, people may be afraid that robots will replace humans in their jobs. This belief is exacerbated by the media that, on one side, raise expectations of robots’ capabilities, while amplifying fears and worries on the other side.
 
 In the next years, due to the increasing request for interaction with people in social environments, academic research and market analyses predict that robots will become more and more “social”. But, at the same time, robots may incur the risk of being perceived as “asocial” as their pervasiveness in everyday environments may become an obstacle to social interaction between humans. Or they may even be rejected as “antisocial” if researchers do not take care to develop robots that behave according to the customs and habits of the communities where they are expected to operate.
 
 To prevent this from happening, robotic researchers can no longer take the luxury of being mere technicians. They must be capable of addressing all the challenges raised by future robot-populated communities in a multidisciplinary way. They need to share their knowledge with the public to make people aware of what robots really are, what expectations we can have from them, the risks we may incur, and the possible mitigation plans.
 
 While being open to any kind of contribution related to Human-Robot Interactive Communication, the RO-MAN 2022 conference will emphasize these aspects of robotic research. How can we create robots capable of being welcomed as our assistants and companions in society while, at the same time, not being perceived as “asocial” or “antisocial?” How can we create robots perceived as facilitators of the natural development of human beings and communities, rather than obstacles?
 
 Contributions from different disciplines, not exclusively related to technological development, will be welcomed as crucial to pave the way to global acceptance of future robots with an informed attitude.
 
 [![](https://assets.underline.io/uploads/markdown_image/1/image/af259abe105b3791c498ae1552d75710.png)](https://drive.google.com/file/d/18w73BZPB_JVOgcrcdZDqYpEupwVt4CnU/view?usp=sharing)

A registration is required to access this event page. If you have not already done so, please use the below link to register for the event. 

[Register Here](http://www.smile.unina.it/ro-man2022/welcome-to-ieee-ro-man-2022/)

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IEEE RO-MAN 2022

31st IEEE International Conference on Robot & Human Interactive Communication
This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.

technical paper

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. This theme also touches upon people's expectations and perceptions of robots, as well as other social, cognitive and cultural factors that will influence human-robot interactions. We will have a special session/track on this topic, invite targeted submissions and include plenary speakers who are specialist in this area. We sincerely hope that this focus will help enlighten the design-thinking of all of us as we fabricate and program our own various systems.

To access RO-MAN Virtual 2021, [please register here.](https://ro-man2021.org/registration/)

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. 

When we humans interact with each other, we adapt our behaviors to the people we interact with. We do this by interpreting subtle cues and signals from them in each interaction. With this paper, we created a robot that uses speech and body movement characteristics to recognize and distinguish between users interacting with it through small duration interactions. We investigate how these characterics are influenced by changing the physical context.

A Minimalistic Approach to User Group Adaptation of Robot Behaviors Using Movement and Speech Analysis

This research has developed a new method for predicting natural human arm movements. It introduces the five-parameter logistic function into this application space and uses supervised learning to predict fingertip trajectories and elbow swivel angles. The method presents small error in an experimental study, improving upon previous methods and verifying its effectiveness.

Human Arm Motion Prediction in Reaching Movements

We present a 3D human activity simulator, ``HOIsim", focusing on Human-Object Interactions (HOIs). Using HOIsim we model two complex activities for ``lunch" and ``breakfast". Furthermore, we introduce methods to meaningfully randomize activity flows and the environment topology, and make a dataset of the 3D pose maps publicly available.

HOIsim: Synthesizing Realistic 3D Human-Object Interaction Data for Human Activity Recognition

This work presents a method for recognition of walking activities and prediction of gait periods using wearable sensors. First, a Convolutional Neural Network (CNN) is used to recognise the walking activity and gait period. Second, the output of the CNN is used by a Predicted Information Gain (PIG) method to predict the next most probable gait period while walking. The output of these two processes are combined to adapt the recognition accuracy of the system. This adaptive combination allows us to achieve an optimal recognition accuracy over time.

Parents’ Views on Using Social Robots for Language Learning

Gesture are a natural modality of human interaction. Smart technologies are seamlessly part of our daily lives, becoming essential to endow them with gesture recognition capbilities to ensure a natural interaction. This work leverages the power of convolutional neural networks proposinga novel spatiotemporal visually interppretable image encoding representation of skeleton data for CNN-based gesture recognition.

Robotic Object Sorting via Deep Reinforcement Learning: a Generalized Approach

In this research, we investigate the use of External Human Machine Interface for delivery robots for expressing their navigational intent. Through a survey, we explore the effectiveness of display and light-based external interfaces in expressing the delivery robots navigational intent.

Understanding robot acceptance/rejection: the SAR model

Social robots have strong potential in health and social care, but the embodiment of these devices is important to ensure acceptability and adoption. Based on a reflection over four studies, we provide insight into the impact of various morphology types. Our results suggest the combination of familiar, zoomorphic appearance with animacy, life-simulation and speech capabilities was an interesting area of research for future robots developed for health and social care.

Morphology of Socially Assistive Robots for Health and Social Care: A Reflection on 24 Months of Research with Anthropomorphic, Zoomorphic and Mechanomorphic Devices

Can a verbal message by a robot change your attitude? More importantly, can it worsen your attitude? Our research study highlights how speech-based appeals
by a robot can successfully influence individuals to trust it with a valuable asset, i.e. their mental health. However, while an emotional appeal by a robot is more effectual
on affective attitudes, it backfires significantly more than a logical appeal when used on cognitive attitudes, leading to trust dissolution. It follows that a robot can, in fact,
successfully arouse emotions in order to persuade. In theory, robots may have an upper hand in executing an effective persuasion attempt compared to humans, who inherently use emotions when they have the intention to persuade.

Would You Trust a Robot with Your Mental Health? The Interaction of Emotion and Logic in Persuasive Backfiring

In this paper, we conduct a full meta-analysis of the existing literature on personality similarity versus dissimilarity (matching/mismatching) and attempt to come to a consensus on if robots with matching personalities are accepted more readily than those with mismatching personalities. In addition, we provide several gaps in this literature worth pursuing.

Social Robot Navigation adapted to Time-dependent Affordance Spaces: a Use Case for Caregiving Centers

A critical issue during HRI is eliciting an intentional stance in the human interactor, who then perceive the agent as an "intelligent" being with full agency towards their own intentions and desires. Eliciting such a stance, however, has proven elusive. We argue for a paradigm shift in our approach to this problem, based on recent evidence from social robotics and digital avatars. To trigger an intentional stance in humans, perhaps our artificial agents need to adopt one about themselves.

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Virtual Tactile Texture Using Electrostatic Friction Display for Natural Materials: The Role of Low and High Frequency Textural Stimuli

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A Minimalistic Approach to User Group Adaptation of Robot Behaviors Using Movement and Speech Analysis

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